Title
Optimal Robust Output Containment of Unknown Heterogeneous Multiagent System Using Off-Policy Reinforcement Learning.
Abstract
This paper investigates optimal robust output containment problem of general linear heterogeneous multiagent systems (MAS) with completely unknown dynamics. A modelbased algorithm using offline policy iteration (PI) is first developed, where the p-copy internal model principle is utilized to address the system parameter variations. This offline PI algorithm requires the nominal model of each agent...
Year
DOI
Venue
2018
10.1109/TCYB.2017.2761878
IEEE Transactions on Cybernetics
Keywords
Field
DocType
Robustness,Heuristic algorithms,Mathematical model,System dynamics,Learning (artificial intelligence),Multi-agent systems,Real-time systems
Mathematical optimization,Control theory,Multi-agent system,Bellman equation,Robustness (computer science),System dynamics,Containment,Mathematics,Internal model,Bounded function,Reinforcement learning
Journal
Volume
Issue
ISSN
48
11
2168-2267
Citations 
PageRank 
References 
8
0.43
32
Authors
4
Name
Order
Citations
PageRank
Shan Zuo1574.52
Yong-Duan Song21949108.61
FRANK L. LEWIS35782402.68
Ali Davoudi434735.39